Henning Lange

Henning Lange is currently a PostDoc in the Applied Maths department at the University of Washington, where they research series expansions and fast summation algorithms in Machine Learning. Their work includes the development of a long-term forecasting method utilizing Fourier series and Koopman theory, and they are actively investigating Fast Taylor Transforms for applications in Computer Vision and Graphics, which has the potential to significantly reduce computational costs. Henning has held various positions, including Applied Scientist at Amazon and Visited Scholar at Carnegie Mellon University, and has earned a PhD from Carnegie Mellon University in Advanced Infrastructure Systems.